Abstract
Social media is a wide source of sharing user’s opinions on different areas. These opinions are known as sentiments. Social media is an application of research for sentiment analysis. Sentiment research gives a direction to the organization about user’s views on their products and services. Many approaches exist for sentiment analysis, and machine learning is one of them. This paper has selected research articles from the year 2013–2019 and studies these to find out the key insights on the most efficient ML techniques used in sentiment analysis. The analysis of the study concludes that the SVM and NB approaches of machine learning are more operationally efficient as compared to others.
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Shrivash, B.K., Verma, D.K., Pandey, P. (2022). An Analysis on Machine Learning Approaches for Sentiment Analysis. In: Somani, A.K., Mundra, A., Doss, R., Bhattacharya, S. (eds) Smart Systems: Innovations in Computing. Smart Innovation, Systems and Technologies, vol 235. Springer, Singapore. https://doi.org/10.1007/978-981-16-2877-1_46
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